The present invention relates generally to AC induction machines and, more particularly, to a system and method for determining a rotor time constant of an AC induction machine.
Electric motors, such as AC induction motors, consume a large percentage of generated electricity capacity. Many applications for this “workhorse” of industry are fan and pump industrial applications. For example, in a typical integrated paper mill, low voltage and medium voltage motors may comprise nearly 70% of all driven electrical loads. Due to the prevalence of these motors in industry, it is paramount that the electric motors be operated reliably and efficiently. Motor design parameters and performance parameters are often required by motor management systems to optimize the control and operations of electric motors. Similarly, motor status monitoring enables the electric motors to operate reliably, and many motor status monitoring techniques look for certain motor design parameters and performance parameters to optimize performance of the motor.
One such motor performance parameter that is helpful in optimizing the control and operations of induction motors is the rotor time constant (rotor resistance), which has a great influence on the dynamic regulation performance and the steady-state error of speed estimation (in a speed sensorless induction machine control). That is, an accurate knowledge of the rotor time constant is essential for both decoupling control and speed estimation. However, it is difficult to identify the rotor time constant, especially when a speed sensor is not available/integrated into the induction motor and/or motor control system. That is, it is recognized that, when the induction motor is working in steady state, simultaneous estimation of speed and rotor time constant (rotor resistance) is not theoretically possible and that, only when the flux magnitude varies with time periodically, can the simultaneous estimation of speed and rotor time constant be achieved.
Various prior art techniques have been employed to estimate the rotor time constant. One such prior art technique utilizes the rotor flux variation during the transient process and a least square strategy to complete the rotor resistance online updating at all speeds. However, such a transient process rarely appears in some industrial applications, and the least square strategy greatly increases the computational burden, making the program more complex. Another known prior art technique utilizes the transient process to identify rotor resistance during a high speed and to compensate the rotor resistance in proportion to the variation of stator resistance during a low speed. This method is also restrained in some applications—for lack of a transient process during motor operation and based on the fact that the thermal drift of stator resistance may be not the same as that of rotor resistance, thus there may be some error to compensate the rotor resistance during low speed.
Another known method for estimating the rotor time constant extracts the voltage and current dynamic high-frequency small signals caused by pulse width modulation (PWM) of the inverter to identify rotor time constant. However, the limitations of this method are that a precision sensor is required to detect small signals, the frequency of which are extremely high, and that a faster AD converter is needed to capture the high frequency information. Additionally, variations of this method use either integral operations or high order differential operations, both of which can further lead to more errors.
Still another known method for estimating the rotor time constant extracts the needed information from the ever-present signal jitter of MRAS error. However, the ever-present small signal of the system is extremely hard to capture. Still another known method for estimating the rotor time constant utilizes an online identification algorithm of rotor time constant based on neural network and fuzzy control. However, such a method needs high amounts of computations and the program is rather complex.
Finally, other known methods for estimating the rotor time constant propose an online updating method based on signal injection. One such method identifies the rotor resistance based on the full-order flux observer and an iterative method is used—leading to a complex computation that has a poor accuracy. Another similar method again identifies the rotor resistance based on the full-order flux observer, but requires two small signals of different frequencies, which increases the difficulties of implementation and can be influenced by speed changes. Another such signal injection method is based on an improved least squares method (fixed trace method), which needs high amounts of computations. Still another such signal injection method operates without differential operations of the small signal, but the identification expression is too complex and needs high amounts of computations. In this method, the injected signal frequency must also be chosen carefully, a reasonable band-pass filter must be designed, and a division by zero is inevitable in identifying the rotor time constant, which greatly degrades the accuracy.
It would therefore be desirable to design a system and method that provides for the simultaneous estimation of the rotor speed and rotor time constant. It would further be desirable for such a system and method to provide such estimations with high accuracy under both no-load or full-load conditions, with such estimations being performed using only amplitudes of the measured signals without considering phase drift (so as to avoid a division by zero at zero-crossing points) and by implementing an algorithm that is less computationally burdensome while still providing accurate estimation results.